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110 lines
3.7 KiB
110 lines
3.7 KiB
"""Prepare Aishell mandarin dataset
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Download, unpack and create manifest files.
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Manifest file is a json-format file with each line containing the
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meta data (i.e. audio filepath, transcript and audio duration)
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of each audio file in the data set.
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import codecs
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import soundfile
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import json
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import argparse
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from data_utils.utility import download, unpack
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DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
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URL_ROOT = 'http://www.openslr.org/resources/33'
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DATA_URL = URL_ROOT + '/data_aishell.tgz'
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MD5_DATA = '2f494334227864a8a8fec932999db9d8'
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument(
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"--target_dir",
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default=DATA_HOME + "/Aishell",
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type=str,
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help="Directory to save the dataset. (default: %(default)s)")
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parser.add_argument(
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"--manifest_prefix",
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default="manifest",
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type=str,
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help="Filepath prefix for output manifests. (default: %(default)s)")
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args = parser.parse_args()
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def create_manifest(data_dir, manifest_path_prefix):
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print("Creating manifest %s ..." % manifest_path_prefix)
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json_lines = []
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transcript_path = os.path.join(data_dir, 'transcript',
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'aishell_transcript_v0.8.txt')
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transcript_dict = {}
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for line in codecs.open(transcript_path, 'r', 'utf-8'):
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line = line.strip()
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if line == '': continue
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audio_id, text = line.split(' ', 1)
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# remove withespace
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text = ''.join(text.split())
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transcript_dict[audio_id] = text
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data_types = ['train', 'dev', 'test']
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for type in data_types:
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audio_dir = os.path.join(data_dir, 'wav', type)
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for subfolder, _, filelist in sorted(os.walk(audio_dir)):
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for fname in filelist:
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audio_path = os.path.join(subfolder, fname)
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audio_id = fname[:-4]
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# if no transcription for audio then skipped
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if audio_id not in transcript_dict:
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continue
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audio_data, samplerate = soundfile.read(audio_path)
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duration = float(len(audio_data) / samplerate)
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text = transcript_dict[audio_id]
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json_lines.append(
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json.dumps(
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{
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'audio_filepath': audio_path,
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'duration': duration,
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'text': text
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},
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ensure_ascii=False))
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manifest_path = manifest_path_prefix + '.' + type
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with codecs.open(manifest_path, 'w', 'utf-8') as fout:
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for line in json_lines:
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fout.write(line + '\n')
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def prepare_dataset(url, md5sum, target_dir, manifest_path):
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"""Download, unpack and create manifest file."""
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data_dir = os.path.join(target_dir, 'data_aishell')
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if not os.path.exists(data_dir):
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filepath = download(url, md5sum, target_dir)
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unpack(filepath, target_dir)
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# unpack all audio tar files
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audio_dir = os.path.join(data_dir, 'wav')
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for subfolder, _, filelist in sorted(os.walk(audio_dir)):
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for ftar in filelist:
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unpack(os.path.join(subfolder, ftar), subfolder, True)
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else:
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print("Skip downloading and unpacking. Data already exists in %s." %
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target_dir)
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create_manifest(data_dir, manifest_path)
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def main():
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if args.target_dir.startswith('~'):
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args.target_dir = os.path.expanduser(args.target_dir)
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prepare_dataset(
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url=DATA_URL,
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md5sum=MD5_DATA,
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target_dir=args.target_dir,
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manifest_path=args.manifest_prefix)
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if __name__ == '__main__':
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main()
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